infinity-project.org Engineering education for today’s classroom 2 Outline How Can We Use Digital...

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Engineering education

for today’s classroom

Outline

• How Can We Use Digital Images?

• A Digital Image is a Matrix

• Manipulating Images

• Improving Images for Robot Eyes

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4.1 How Can We Use Digital Images?

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Engineering education

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The Power of Digital Images

• It is easier and easier to acquire or make digital imagesDigital cameras and scanners

• Chief advantage over analog (e.g. film) images: Easy to change

• How might we change images?

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Image Softening and Blurring

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Image Sharpening

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Finding Edges in Images

• Edges in images usually define solid objects in our 3D world

• Finding edges is a first step to navigation and manipulation

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Subtracting Images

•Image subtraction is a simple way to find differences between two images

•Useful for security, recognition, and navigation applications

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Image Segmentation

• Segmentation: Dividing images into regions

• Applications Identifying

foreground vs. background

Finding objects using only one image

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4.2 A Digital Image Is a Matrix

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Digital Images are Matrices

• Matrix: An array of numbers

A =

101134

5610

751214 3 rows and 4 columns

• Elements: A(i,j) , i and j are integers

Examples: A(2,3) = 6,A(1,4) = 7, A(3,4) = 10

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Classes of Image Manipulation

1. Mapping: Pixel-by-pixel operations2. Arithmetic Combination of Two Images:

e.g. addition, multiplication3. Filtering: Operations on groups of pixels

in an image (neighborhood operation)Fact: Almost all applications are made up of

simple combinations of these manipulations

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Image Mapping

• All of the form B(i,j) = {function of

A(i,j)}

where B(i,j) is the output image

• Many familiar effects:Brightness, Contrast, Negative,

Thresholding, Gamma Correction

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k = -50

k = 50

Brightness Mapping

B(i,j) = A(i,j) + kk = constant

(expressed as a table)

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Example: Brightness Mapping

Original 24-bit image

Each color increased

by 60

Each color decreased

by 60

Green and blue +60, red -60

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Contrast Mapping

• Formula: B(i,j) = s • A(i,j) If s > 1, contrast is increased If s < 1, contrast is decreased

• Need to quantize after multiplying, as s • A(i,j) may not be an integer

• Aside: This setting is found on most TV sets

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Contrast Mapping (cont.)

s > 1

s < 1

s > 1 and k < 0

s < 1 and k > 0

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Example: Contrast and Brightness

• Formula: B(i,j) = s • A(i,j) + k

• This is easy to do!

Higher contrast

Higher contrast

with lower

brightness

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Example: Contrast and Brightness

• Given the 4-bit grayscale image

A =

101134

5610

751214

• Compute the image with a contrast of 1.5 and a

brightness of 2

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Solution: Contrast and Brightness

• Answer: B(i,j) = 1.5•A(i,j) + 2

B = 151578

101142

13101515 Quantization causes values such as 9.5 and 3.5 to be rounded up

Image is clipped at 15

(Why?)

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Infinity Project Experiment – 4.1

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Brightness and Contrast Grayscale

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Brightness and Contrast Color Image

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Brightness and Contrast Color Camera

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Brightness and Contrast Cascade